Plutus: Benchmarking Large Language Models in Low-Resource Greek Finance
Xueqing Peng, Triantafillos Papadopoulos, Efstathia Soufleri,, Polydoros Giannouris, Ruoyu Xiang, Yan Wang, Lingfei Qian, Jimin Huang,, Qianqian Xie, Sophia Ananiadou

TL;DR
This paper introduces Plutus-ben, a Greek financial NLP benchmark, and Plutus-8B, a Greek financial LLM, to evaluate and advance Greek-specific financial language understanding, revealing significant challenges and the need for domain expertise.
Contribution
The paper presents the first Greek financial NLP benchmark and a Greek financial LLM, along with new datasets, to facilitate systematic evaluation and development in Greek financial language processing.
Findings
Greek financial NLP is challenging due to linguistic complexity.
Cross-lingual transfer has limited effectiveness for Greek financial tasks.
Greek-trained models require financial domain expertise.
Abstract
Despite Greece's pivotal role in the global economy, large language models (LLMs) remain underexplored for Greek financial context due to the linguistic complexity of Greek and the scarcity of domain-specific datasets. Previous efforts in multilingual financial natural language processing (NLP) have exposed considerable performance disparities, yet no dedicated Greek financial benchmarks or Greek-specific financial LLMs have been developed until now. To bridge this gap, we introduce Plutus-ben, the first Greek Financial Evaluation Benchmark, and Plutus-8B, the pioneering Greek Financial LLM, fine-tuned with Greek domain-specific data. Plutus-ben addresses five core financial NLP tasks in Greek: numeric and textual named entity recognition, question answering, abstractive summarization, and topic classification, thereby facilitating systematic and reproducible LLM assessments. To…
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Code & Models
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Taxonomy
TopicsStock Market Forecasting Methods · Topic Modeling · Machine Learning in Healthcare
